Predictive analytics in supply chains MCQs in Supply Chain

MCQs on Predictive Analytics in Supply Chains

Which of the following best describes predictive analytics?
- A. Analyzing past data to find patterns
- B. Using historical data to predict future outcomes
- C. Real-time processing of data
- D. Creating visual representations of data
- Answer: B. Using historical data to predict future outcomes
What is a primary benefit of predictive analytics in supply chain management?
- A. Reducing manual labor
- B. Enhancing product quality
- C. Improving demand forecasting accuracy
- D. Lowering transportation costs
- Answer: C. Improving demand forecasting accuracy
Which technique is commonly used in predictive analytics for supply chains?
- A. Linear regression
- B. Cluster analysis
- C. Sentiment analysis
- D. Real-time processing
- Answer: A. Linear regression
What kind of data is most crucial for effective predictive analytics in supply chains?
- A. Financial data
- B. Historical sales data
- C. Social media data
- D. Employee data
- Answer: B. Historical sales data
Which of the following is a challenge in implementing predictive analytics in supply chains?
- A. Lack of skilled personnel
- B. High-quality data availability
- C. Low computational power requirements
- D. Simple integration with existing systems
- Answer: A. Lack of skilled personnel
In predictive analytics, what is ‘overfitting’?
- A. A model that fits the training data too well but performs poorly on new data
- B. A model that generalizes well to new data
- C. The process of simplifying a model
- D. The technique of splitting data into training and testing sets
- Answer: A. A model that fits the training data too well but performs poorly on new data
What role does machine learning play in predictive analytics for supply chains?
- A. Automates data collection
- B. Identifies patterns and makes predictions
- C. Visualizes data trends
- D. Manages inventory
- Answer: B. Identifies patterns and makes predictions
Which predictive analytics model is commonly used to predict product demand in supply chains?
- A. Decision trees
- B. Neural networks
- C. Time series forecasting
- D. Association rule learning
- Answer: C. Time series forecasting
What is the primary goal of using predictive analytics in supply chain inventory management?
- A. Increasing stock levels
- B. Decreasing the variety of products
- C. Optimizing inventory levels
- D. Enhancing product design
- Answer: C. Optimizing inventory levels
Predictive analytics can help in identifying which of the following supply chain risks?
- A. Currency fluctuation
- B. Supplier failure
- C. Transportation delays
- D. All of the above
- Answer: D. All of the above
Which of the following is not a step in the predictive analytics process?
- A. Data collection
- B. Data cleansing
- C. Model deployment
- D. Sales execution
- Answer: D. Sales execution
In the context of supply chain, what is ‘demand forecasting’?
- A. Predicting future customer demand
- B. Tracking current inventory levels
- C. Estimating product shelf life
- D. Analyzing sales channels
- Answer: A. Predicting future customer demand
Which software tool is widely used for predictive analytics in supply chains?
- A. SAP
- B. Tableau
- C. Microsoft Excel
- D. IBM SPSS
- Answer: D. IBM SPSS
Predictive analytics in supply chains can significantly impact which of the following areas?
- A. Marketing campaigns
- B. Customer service
- C. Supplier relationship management
- D. Product pricing
- Answer: C. Supplier relationship management
Which of the following is a common outcome of effective predictive analytics in supply chains?
- A. Increased lead times
- B. Reduced inventory carrying costs
- C. Higher operational costs
- D. Increased product defects
- Answer: B. Reduced inventory carrying costs

Predictive analytics in supply chains MCQs in Supply Chain

MCQs on Predictive Analytics in Supply Chains

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